1. Field of the Invention
The present invention concerns a tomographical image reconstruction method for generation of an image of an examination subject. The present invention also concerns an imaging device operating according to such a method.
2. Description of the Prior Art
Tomographical image reconstruction is a computerized method that allows a two-dimensional image or a three-dimensional volume image of the examination subject to be generated from projection (two-dimensional) data acquired at different projection angles.
For this purpose, a number of mathematical algorithms are known, among which include iterative, algebraic reconstruction methods that have proven to be particularly suitable for conventional computed tomography (CT) operating with x-ray radiation as well as for tomosynthesis (likewise operating with x-ray radiation).
Tomosynthesis is an imaging method in which individual images or projection data of an examination subject are acquired in a number of different projection directions with a digital x-ray detector. Through image reconstruction methods, a three-dimensional image data set can be generated from these individual digital images (i.e. from the image data belonging to these individual images) acquired from different projection angles in a limited angle range (for example between −25° and +25° relative to the normal of the acquisition surface of the x-ray detector). The three-dimensional image data set is composed of a number of slice images that respectively render a slice of the breast oriented parallel to the acquisition surface of the x-ray detector, for example. Tomosynthesis is used to generate three-dimensional x-ray images of the breast, for example.
The tomosynthetic slice images generated with an iterative algebraic reconstruction method exhibit a very high similarity to conventional mammography images with regard to the ability to differentiate between dense and less dense tissue, such that their interpretation by radiologists familiar with such mammography images is made easier.
The long computation times incurred with iterative algebraic reconstruction methods, however, are disadvantageous. For this reason, filtered back projection is normally used as a reconstruction method, both in conventional CT and in tomosynthesis.
In filtered back projection, the metadata provided by the x-ray detector are filtered and projected back to a volume matrix—the digital, three-dimensional image of a partial volume of the subject. It is one of the most promising reconstruction methods since it is based on an analytical algorithm that can be derived from the scan geometry and is numerically very efficient and stable.
A significant problem in filtered back projection is the provision of suitable filters with which it is possible for the physical measurement method that is used and the geometry that is used (for example conventional CT or tomosynthesis with limited angle range) to generate tomographic images with high clarity in order to differentiate benign from malignant variations and in order to be able to reduce the number of incorrect findings, i.e. the number of the suspected findings that are caused by non-malignant variations and the number of undetected malignant tumors.
A particularly promising approach to this is known from DE 10 2005 050 917 A1, in which a discrete filter kernel suitable for filtered back projection is calculated with an iterative algebraic reconstruction method. These discrete filter kernels can then be inserted into the filtered back projection instead of typical filter kernels. The desired image quality therefore results in a short calculation time. The discrete filter kernels calculated with this method are generated with a test subject (for example a wireframe model) and optimized with regard to this test subject, but not with regard to a real examination subject and the concrete, diagnostic question. Such an optimization would require the use of a number of such discrete filter kernels calculated via iterative, algebraic reconstruction, with correspondingly high measurement and calculation cost.